May 25 - July 30
Spatial Analysis of Tornado Vulnerability Trends in Oklahoma and Northern Texas
Eric Hout, May Yuan, John MacIntosh, and Chris Weaver
What is already known:
- Previous work on vulnerability to disasters has been incredibly complex, both within the meteorological and outside of it, with the meaning of "vulnerability" changing between disciplines.
- When vulnerability to disasters has been analyzed in meteorology, research has tended to focus on how single variables, such as population density or structure type, affect vulnerability. A more aggregated approach should to be taken care of vulnerability in the meteorological community, with analysis focusing on how several factors all at once can impact vulnerability.
What this study adds:
- A definition is proposed on spatial vulnerability to tornadoes incorporating all factors contributing to a location's vulnerability to a particular tornado.
- Distinct patterns of similar spatial vulnerability trends over time are shown throughout Oklahoma and parts of Texas.
Abstract:
Determination of effective ways to reduce vulnerability from tornadoes is one of the fundamental drivers for tornado research. This study analyzes spatial vulnerability in the context of past tornado events with aims to enhance the understanding of tornado casualties in Oklahoma and Northern Texas. Many previous studies on tornado vulnerability have provided insight on how individual factors influence overall social and spatial vulnerability. However, few studies have been conducted to evaluate the aggregated effect on vulnerability when these factors coincide. Additionally, a definition of vulnerability has been absent from the meteorological literature. Thus, to provide a more comprehensive view of vulnerability, this study proposes a mathematical definition for spatial vulnerability, and then uses tornado casualty data from 1950 through 2009 to calculate vulnerability on a county level for seven time periods. Overall vulnerability trends are then calculated and visualized by averaging changes and by k-means clustering. This study shows the existence of spatial patterns in vulnerability between counties both when analyzing each individual F-scale and when all F-scales are combined. These spatial patterns are likely caused by the existence of multiple variables working together.